TRACING THE DEFORMED MIDLINE ON BRAIN CT

Author:

LIAO CHUN-CHIH123,CHIANG I-JEN13,XIAO FUREN34,WONG JAU-MIN34

Affiliation:

1. Graduate Institute of Medical Informatics, Taipei Medical University, Taiwan

2. Taipei Hospital, Department of Health, Taiwan

3. Institute of Biomedical Engineering, National Taiwan University, Taiwan

4. National Taiwan University Hospital, Taipei, Taiwan

Abstract

Midline shift (MLS) is the most important quantitative feature clinicians use to evaluate the severity of brain compression by various pathologies. We proposed a model of the deformed midline according to the biomechanical properties of different types of intracranial tissue. The model comprised three segments. The upper and lower straight segments represented parts of the tough meninges separating two hemispheres, and the central curved segment, formed by a quadratic Bezier curve, represented the intervening soft brain tissue. For each point of the model, the intensity difference was calculated over 48 adjacent point pairs at each side. The deformed midline was considered ideal as summed square of the difference across all midline points approaches global minimum, simulating maximal bilateral symmetry. Genetic algorithm was applied to optimize the values of the three control points of the Bezier curve. Our system was tested on images containing various pathologies from 81 consecutive patients treated in a single institute over one-year period. The deformed midlines itself as well as the amount of midline shift were evaluated by human experts, with satisfactory results.

Publisher

National Taiwan University

Subject

Biomedical Engineering,Bioengineering,Biophysics

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1. Dual-path U-transformer network for assessment of brain midline shift in hemorrhagic stroke;Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023);2024-03-25

2. Automatic Brain Midline Surface Delineation on 3D CT Images With Intracranial Hemorrhage;IEEE Transactions on Medical Imaging;2022-09

3. Detection of Midline Shift from CT Scans to Predict Outcome in Patients with Head Injuries;International Journal of Biomedicine;2021-03-05

4. Segmentation-Based Method Combined with Dynamic Programming for Brain Midline Delineation;2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI);2020-04

5. Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation;Medical Image Computing and Computer Assisted Intervention – MICCAI 2020;2020

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